Three Thinking Skills You Need To Survive The AI Revolution

I recently had a sobering moment during a strategy session with a tech CEO. As we reviewed his enterprise’s artificial intelligence (AI) roadmap, the realization hit us both: within 18 months, nearly 40 percent of its operational tasks could likely be automated.

The tension in the room was palpable. Not because AI is coming (we all know that), but because we suddenly understood how unprepared most of us are for what happens next.

AI will soon know everything we know. It will be faster at many tasks we perform daily. No skill seems sacred.

But here’s what I’ve learned working with dozens of leaders navigating this transition: in the AI era, your competitive edge isn’t what you know – but how you think.

Why Most AI Strategies Are Missing The Point

Many organizations are approaching AI backward. They’re asking: “How can we use AI to do what we already do, but faster?”

That’s like asking horses to pull cars instead of leveraging the combustion engine. Optimizing processes that shouldn’t exist isn’t a future-proof strategy.

I see this limited thinking in boardrooms across industries. Last month, a professional services firm’s director proudly showed me their AI strategy, essentially a plan to automate report generation. When I asked how they were preparing their teams to think differently in an AI-augmented world, I saw blank stares.

This hesitation makes sense. Leaders have grown cautious after a parade of over-hyped technologies. Remember the metaverse? Non-fungible tokens (NFTs)? Both were supposed to revolutionize business and commerce, yet neither delivered on their grand promises. This creates a paradox: companies dismiss AI as just another bubble, or they frantically adopt it without a strategic vision. The truth is that AI isn’t a fad, and it’s also not the doomsday scenario some predict. The real winners won’t be those who panic and jump in blindly, nor those who ignore it entirely. Success will come to those who navigate between these extremes by developing new ways of thinking about what’s possible when humans and AI collaborate.

The Three Thinking Skills That Will Save Your Career

Through my work in helping organizations navigate technological disruption, I’ve identified three thinking skills that are becoming the ultimate survival tools in the AI era.

1. Design Thinking: Finding Problems AI Can’t See

Design thinking is a human-centered approach to problem-solving and innovation that integrates human needs, technological possibilities, and business requirements. It’s about understanding users deeply and solving their real problems, not just the symptoms.

AI excels at solving known problems. What it can’t do well (yet) is discover unmet, unarticulated human needs, and connect disparate dots to frame better problems.

I recently observed a fascinating contrast between two product teams. Team A fed their requirements directly into AI systems to build faster. Team B spent several days in the field with customers, uncovering hidden frustrations that no algorithm could have identified. Six months later, Team B’s solution attracted 3x the customer engagement.

So, how do you develop this skill? Here’s a primer:

• Spend time directly observing people’s behavior, not just listening to what they say.
• Practice reframing problems before jumping to solutions.
• Ask “what if?” and “why?” questions relentlessly.
• Think like a traveler, be an anthropologist and detective.

2. Systems Thinking:

Seeing The Ripple Effects

Systems thinking is understanding how different components within a complex arrangement influence one another. Rather than analyzing isolated parts, it focuses on how the parts interact within the whole, revealing patterns and relationships that would otherwise remain invisible.

AI operates within the systems we design. But it rarely understands how changing one element affects everything else.

Last year, a retail client implemented an AI-powered inventory system that brilliantly optimized stock levels. Three months later, they were facing a customer service crisis. Why? The system hadn’t accounted for how inventory changes affect delivery expectations, staff scheduling, and customer communications.

Here’s how you can develop such a framework for thought:

• Learn to identify causal loops and leverage points in your organization.
• Remind yourself that the whole is greater than the sum of its parts.
• Ask “and then what happens?” at least three times for every decision.
• Build small experiments to test systemic effects before full implementation.

3. Futures Thinking:

Shaping Tomorrow Instead Of Reacting To It

Futures thinking is a structured approach to exploring possible futures and their implications. Unlike prediction, which assumes a single outcome, it involves mapping multiple scenarios to prepare for various possibilities and actively shaping your desired outcomes.

While everyone else focuses on using AI for today’s challenges, the real winners are already anticipating and shaping what comes next.

A manufacturing CEO I advise – very much the early adopter type – started scenario planning how AI would transform her industry five years ago. While competitors scrambled to implement basic automation, she had already positioned her company for the second wave: AI-human collaborative manufacturing. The result? They’re now at least two years ahead of their industry.

So, how do you develop your futures thinking capabilities?

• Dedicate time each week to explore emerging trends.
• Build multiple scenarios, not just best/worst cases.
• Identify “no regrets” moves that work across futures.
• Create small bets that test different potential futures.

Start Thinking Differently Today

Here’s what I tell every executive worried about AI: the technology itself isn’t your competitive advantage. Your unique human thinking is.

Begin with these practical steps:

• Dedicate time to thinking: Block 2-4 hours weekly for pure thinking and exploration.
• Build thinking teams: Include people from different backgrounds and thinking styles.
• Reward thoughtful failure: Acknowledge when teams learn from thoughtful risks.
• Challenge assumptions: Ask what beliefs about your industry might no longer be true.

The AI revolution is coming whether we’re ready or not. But it’s not about machines replacing humans. It’s about humans working alongside machines to achieve what neither could accomplish alone.

Your move.

About The Author

Marc Mekki is an innovation strategist, keynote speaker, and executive advisor specializing in digital transformation, design thinking, systems thinking, and creative leadership. He helps global businesses and government organizations navigate disruption, build future-ready strategies, and rethink how they solve problems and spot opportunities.

This article first appeared in the March issue of Inc. Arabia magazine. To read the full issue online, click here.